Parametric Embedding for Class Visualization

Iwata, Tomoharu, Saito, Kazumi, Ueda, Naonori, Stromsten, Sean, Griffiths, Thomas L., Tenenbaum, Joshua B.

Neural Information Processing Systems 

In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model.

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